{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/Owsiak/Dropbox/Diehl Greig and Owsiak/II 2019/Individual Article/Final Files/Log File for Trajectories - Theory and Evidence.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}29 Jul 2020, 12:05:28

{com}. do "/var/folders/85/m7mmkq454hscrr59tsws9fq00000gn/T//SD00372.000000"
{txt}
{com}. * Do File for: Owsiak, Andrew P. 2021. Conflict Management Trajectories: Theory and Evidence.
. * Last updated: 9 June 2020
. *Includes replication for main text and appendices.
. 
. use "Replication Data for Trajectories - Theory and Evidence.dta", clear
{txt}
{com}. 
. 
. *Table 1
. *Text only. No replication.
. 
. 
. *Table 2
. tab Ycat if ngo==0 & unique==1

   {txt}Int Type {c |}
  1=verbal, {c |}
2=mediation {c |}
 , 3=legal, {c |}
   4=admin, {c |}
 5=peace op {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        323       47.50       47.50
{txt}          2 {c |}{res}        279       41.03       88.53
{txt}          3 {c |}{res}         13        1.91       90.44
{txt}          4 {c |}{res}         20        2.94       93.38
{txt}          5 {c |}{res}         45        6.62      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}        680      100.00
{txt}
{com}. tab Ycat stateint if ngo==0 & unique==1, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

  Int Type {c |}
 1=verbal, {c |}
2=mediatio {c |}
        n, {c |}   State
  3=legal, {c |} Interventi
  4=admin, {c |}     on
5=peace op {c |}         1 {c |}     Total
{hline 11}{c +}{hline 11}{c +}{hline 10}
         1 {c |}{res}       188 {txt}{c |}{res}       188 
           {txt}{c |}{res}     54.34 {txt}{c |}{res}     54.34 
{txt}{hline 11}{c +}{hline 11}{c +}{hline 10}
         2 {c |}{res}       141 {txt}{c |}{res}       141 
           {txt}{c |}{res}     40.75 {txt}{c |}{res}     40.75 
{txt}{hline 11}{c +}{hline 11}{c +}{hline 10}
         3 {c |}{res}         1 {txt}{c |}{res}         1 
           {txt}{c |}{res}      0.29 {txt}{c |}{res}      0.29 
{txt}{hline 11}{c +}{hline 11}{c +}{hline 10}
         4 {c |}{res}         6 {txt}{c |}{res}         6 
           {txt}{c |}{res}      1.73 {txt}{c |}{res}      1.73 
{txt}{hline 11}{c +}{hline 11}{c +}{hline 10}
         5 {c |}{res}        10 {txt}{c |}{res}        10 
           {txt}{c |}{res}      2.89 {txt}{c |}{res}      2.89 
{txt}{hline 11}{c +}{hline 11}{c +}{hline 10}
     Total {c |}{res}       346 {txt}{c |}{res}       346 
           {txt}{c |}{res}    100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. tab Ycat coalint if ngo==0 & unique==1, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

  Int Type {c |}
 1=verbal, {c |}
2=mediatio {c |}
        n, {c |}
  3=legal, {c |}       Coalition
  4=admin, {c |}     Intervention
5=peace op {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         1 {c |}{res}       303         20 {txt}{c |}{res}       323 
           {txt}{c |}{res}     48.10      40.00 {txt}{c |}{res}     47.50 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         2 {c |}{res}       255         24 {txt}{c |}{res}       279 
           {txt}{c |}{res}     40.48      48.00 {txt}{c |}{res}     41.03 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         3 {c |}{res}        12          1 {txt}{c |}{res}        13 
           {txt}{c |}{res}      1.90       2.00 {txt}{c |}{res}      1.91 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         4 {c |}{res}        20          0 {txt}{c |}{res}        20 
           {txt}{c |}{res}      3.17       0.00 {txt}{c |}{res}      2.94 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         5 {c |}{res}        40          5 {txt}{c |}{res}        45 
           {txt}{c |}{res}      6.35      10.00 {txt}{c |}{res}      6.62 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       630         50 {txt}{c |}{res}       680 
           {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. tab Ycat igoint if ngo==0 & unique==1, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

  Int Type {c |}
 1=verbal, {c |}
2=mediatio {c |}
        n, {c |}
  3=legal, {c |}
  4=admin, {c |}   IGO Intervention
5=peace op {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         1 {c |}{res}       187        136 {txt}{c |}{res}       323 
           {txt}{c |}{res}     54.68      40.24 {txt}{c |}{res}     47.50 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         2 {c |}{res}       138        141 {txt}{c |}{res}       279 
           {txt}{c |}{res}     40.35      41.72 {txt}{c |}{res}     41.03 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         3 {c |}{res}         1         12 {txt}{c |}{res}        13 
           {txt}{c |}{res}      0.29       3.55 {txt}{c |}{res}      1.91 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         4 {c |}{res}         6         14 {txt}{c |}{res}        20 
           {txt}{c |}{res}      1.75       4.14 {txt}{c |}{res}      2.94 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         5 {c |}{res}        10         35 {txt}{c |}{res}        45 
           {txt}{c |}{res}      2.92      10.36 {txt}{c |}{res}      6.62 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}       342        338 {txt}{c |}{res}       680 
           {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 
{txt}
{com}. 
. 
. *Table B1
. *Model 1
. oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-974.50841}  
Iteration 1:{space 3}log pseudolikelihood = {res: -934.0052}  
Iteration 2:{space 3}log pseudolikelihood = {res:-933.96828}  
Iteration 3:{space 3}log pseudolikelihood = {res:-933.96827}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       872
{txt}{col 49}Wald chi2({res}3{txt}){col 67}= {res}     22.35
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0001
{txt}Log pseudolikelihood = {res}-933.96827{txt}{col 49}Pseudo R2{col 67}= {res}    0.0416

{txt}{ralign 78:(Std. Err. adjusted for {res:121} clusters in precmid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        Ycat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}Ystar1 {c |}{col 14}{res}{space 2}-.6389158{col 26}{space 2} .2269135{col 37}{space 1}   -2.82{col 46}{space 3}0.005{col 54}{space 4}-1.083658{col 67}{space 3}-.1941736
{txt}{space 6}Ystar3 {c |}{col 14}{res}{space 2}-.5414473{col 26}{space 2} .2085027{col 37}{space 1}   -2.60{col 46}{space 3}0.009{col 54}{space 4}-.9501051{col 67}{space 3}-.1327895
{txt}{space 6}Ystar4 {c |}{col 14}{res}{space 2} .5047362{col 26}{space 2} .2614142{col 37}{space 1}    1.93{col 46}{space 3}0.054{col 54}{space 4}-.0076263{col 67}{space 3} 1.017099
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-.4328009{col 26}{space 2} .2603317{col 54}{space 4}-.9430417{col 67}{space 3} .0774399
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2}  .833718{col 26}{space 2} .2343059{col 54}{space 4} .3744868{col 67}{space 3} 1.292949
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} .9284713{col 26}{space 2}  .217263{col 54}{space 4} .5026437{col 67}{space 3} 1.354299
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} 1.134966{col 26}{space 2} .2065897{col 54}{space 4} .7300578{col 67}{space 3} 1.539875
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Model 2
. oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & year<1990), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-573.07656}  
Iteration 1:{space 3}log pseudolikelihood = {res:-564.14534}  
Iteration 2:{space 3}log pseudolikelihood = {res:-564.14317}  
Iteration 3:{space 3}log pseudolikelihood = {res:-564.14317}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       504
{txt}{col 49}Wald chi2({res}3{txt}){col 67}= {res}      4.69
{txt}{col 49}Prob > chi2{col 67}= {res}    0.1957
{txt}Log pseudolikelihood = {res}-564.14317{txt}{col 49}Pseudo R2{col 67}= {res}    0.0156

{txt}{ralign 78:(Std. Err. adjusted for {res:83} clusters in precmid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        Ycat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}Ystar1 {c |}{col 14}{res}{space 2} -.368104{col 26}{space 2} .2995979{col 37}{space 1}   -1.23{col 46}{space 3}0.219{col 54}{space 4}-.9553052{col 67}{space 3} .2190971
{txt}{space 6}Ystar3 {c |}{col 14}{res}{space 2} -.355545{col 26}{space 2} .3075121{col 37}{space 1}   -1.16{col 46}{space 3}0.248{col 54}{space 4}-.9582577{col 67}{space 3} .2471676
{txt}{space 6}Ystar4 {c |}{col 14}{res}{space 2}  .242084{col 26}{space 2} .3786993{col 37}{space 1}    0.64{col 46}{space 3}0.523{col 54}{space 4} -.500153{col 67}{space 3}  .984321
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-.3948456{col 26}{space 2} .2852906{col 54}{space 4}-.9540049{col 67}{space 3} .1643137
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2} .8047703{col 26}{space 2}  .260013{col 54}{space 4} .2951543{col 67}{space 3} 1.314386
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} .9078961{col 26}{space 2} .2217579{col 54}{space 4} .4732587{col 67}{space 3} 1.342534
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} 1.067639{col 26}{space 2} .2051916{col 54}{space 4} .6654709{col 67}{space 3} 1.469807
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Model 3
. oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & year>1989), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-399.26925}  
Iteration 1:{space 3}log pseudolikelihood = {res: -357.4213}  
Iteration 2:{space 3}log pseudolikelihood = {res:-357.24524}  
Iteration 3:{space 3}log pseudolikelihood = {res:-357.24516}  
Iteration 4:{space 3}log pseudolikelihood = {res:-357.24516}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       368
{txt}{col 49}Wald chi2({res}3{txt}){col 67}= {res}     39.77
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-357.24516{txt}{col 49}Pseudo R2{col 67}= {res}    0.1053

{txt}{ralign 78:(Std. Err. adjusted for {res:38} clusters in precmid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        Ycat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}Ystar1 {c |}{col 14}{res}{space 2}-1.056432{col 26}{space 2} .2211642{col 37}{space 1}   -4.78{col 46}{space 3}0.000{col 54}{space 4}-1.489906{col 67}{space 3}-.6229584
{txt}{space 6}Ystar3 {c |}{col 14}{res}{space 2}-.7674168{col 26}{space 2}  .300459{col 37}{space 1}   -2.55{col 46}{space 3}0.011{col 54}{space 4}-1.356306{col 67}{space 3}-.1785279
{txt}{space 6}Ystar4 {c |}{col 14}{res}{space 2} .8236184{col 26}{space 2} .4044544{col 37}{space 1}    2.04{col 46}{space 3}0.042{col 54}{space 4} .0309023{col 67}{space 3} 1.616335
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-.5272474{col 26}{space 2} .5298921{col 54}{space 4}-1.565817{col 67}{space 3} .5113221
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2} .8906313{col 26}{space 2} .5311717{col 54}{space 4}-.1504461{col 67}{space 3} 1.931709
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} .9726829{col 26}{space 2} .5370296{col 54}{space 4}-.0798757{col 67}{space 3} 2.025241
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} 1.279144{col 26}{space 2} .5468298{col 54}{space 4} .2073774{col 67}{space 3} 2.350911
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. *Table 3
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-974.50841
{txt}Iteration 1:   log pseudolikelihood = {res} -934.0052
{txt}Iteration 2:   log pseudolikelihood = {res}-933.96828

{txt}Ordered probit estimates                          Number of obs   = {res}       872
                                                  {txt}Wald chi2({res}3{txt})    = {res}     22.35
                                                  {txt}Prob > chi2     = {res}    0.0001
{txt}Log pseudolikelihood = {res}-933.96828                 {txt}Pseudo R2       = {res}    0.0416

                              {txt}(Std. Err. adjusted for {res}121{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res}-.6389158   .2269108    -2.82   0.005    -1.083653   -.1941788
      {txt}Ystar3 {c |}  {res}-.5414473   .2085019    -2.60   0.009    -.9501035   -.1327912
      {txt}Ystar4 {c |}  {res} .5047362   .2614128     1.93   0.054    -.0076235    1.017096
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-.4328009   .2603277          {txt}(Ancillary parameters)
       _cut2 {c |}  {res}  .833718   .2343047 
       {txt}_cut3 {c |}  {res} .9284713    .217261 
       {txt}_cut4 {c |}  {res} 1.134966   .2065875 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 14% 28% 42% 57% 71% 85% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .5940097     .0491447     .4965753     .690128
                {txt}Pr(Ycat=2) |  {res} .3371558     .0380282     .2614559     .412167
                {txt}Pr(Ycat=3) |  {res} .0111563     .0052103     .0014149    .0222103
                {txt}Pr(Ycat=4) |  {res} .0194169     .0069756     .0079625    .0349273
                {txt}Pr(Ycat=5) |  {res} .0382613     .0169646     .0138095    .0811753
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .3494087     .0548236     .2515629    .4642508
                {txt}Pr(Ycat=2) |  {res} .4578044     .0436791     .3738436    .5423364
                {txt}Pr(Ycat=3) |  {res}  .024826     .0114296     .0027238    .0475849
                {txt}Pr(Ycat=4) |  {res} .0470239      .016219     .0179186    .0807137
                {txt}Pr(Ycat=5) |  {res}  .120937     .0188776     .0867583    .1585599
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .1834067     .0598948     .0866047    .3183015
                {txt}Pr(Ycat=2) |  {res} .4464587     .0437026     .3509177    .5288651
                {txt}Pr(Ycat=3) |  {res} .0344732     .0156422     .0042663    .0651273
                {txt}Pr(Ycat=4) |  {res} .0707139     .0238128     .0285813    .1191887
                {txt}Pr(Ycat=5) |  {res} .2649476     .0668329     .1512117    .4167751
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .3401288     .0945891     .1734317    .5401757
                {txt}Pr(Ycat=2) |  {res} .4523557     .0487972     .3478085    .5414741
                {txt}Pr(Ycat=3) |  {res} .0263167     .0140225     .0022025    .0551228
                {txt}Pr(Ycat=4) |  {res} .0490764     .0198438     .0153964    .0934228
                {txt}Pr(Ycat=5) |  {res} .1321224     .0438617     .0590551    .2284271
{txt}
{com}. drop b1-b7
{txt}
{com}. 
. 
. *Table B2
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & year<1990), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-573.07656
{txt}Iteration 1:   log pseudolikelihood = {res}-564.14534
{txt}Iteration 2:   log pseudolikelihood = {res}-564.14317

{txt}Ordered probit estimates                          Number of obs   = {res}       504
                                                  {txt}Wald chi2({res}3{txt})    = {res}      4.69
                                                  {txt}Prob > chi2     = {res}    0.1957
{txt}Log pseudolikelihood = {res}-564.14317                 {txt}Pseudo R2       = {res}    0.0156

                               {txt}(Std. Err. adjusted for {res}83{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res} -.368104   .2995977    -1.23   0.219    -.9553048    .2190967
      {txt}Ystar3 {c |}  {res} -.355545    .307512    -1.16   0.248    -.9582574    .2471674
      {txt}Ystar4 {c |}  {res}  .242084   .3786991     0.64   0.523    -.5001525    .9843205
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-.3948456   .2852902          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .8047703   .2600129 
       {txt}_cut3 {c |}  {res} .9078961   .2217577 
       {txt}_cut4 {c |}  {res} 1.067639   .2051914 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 14% 28% 42% 57% 71% 85% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .5327755     .0540144     .4254277    .6381665
                {txt}Pr(Ycat=2) |  {res} .3633211     .0362161     .2936151    .4350809
                {txt}Pr(Ycat=3) |  {res} .0156464     .0089362    -.0035739    .0334044
                {txt}Pr(Ycat=4) |  {res} .0210472     .0099586     .0024165      .04264
                {txt}Pr(Ycat=5) |  {res} .0672098     .0322941     .0214988    .1486918
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .3938474     .0761807     .2559025    .5490881
                {txt}Pr(Ycat=2) |  {res}  .424859     .0489697     .3244266    .5159661
                {txt}Pr(Ycat=3) |  {res} .0262082     .0166667    -.0037113    .0630881
                {txt}Pr(Ycat=4) |  {res} .0354855     .0184998     .0029649    .0753335
                {txt}Pr(Ycat=5) |  {res} .1195999     .0223585     .0809576    .1660826
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .2757236     .0957604     .1111341    .4884425
                {txt}Pr(Ycat=2) |  {res} .4343371     .0450249     .3381065    .5171188
                {txt}Pr(Ycat=3) |  {res} .0334173     .0210516    -.0043443    .0789997
                {txt}Pr(Ycat=4) |  {res} .0471386     .0243365     .0034437    .1001766
                {txt}Pr(Ycat=5) |  {res} .2093834     .0775377     .0863053    .3947576
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res}  .354612     .1028498      .174514    .5655716
                {txt}Pr(Ycat=2) |  {res} .4287068     .0498716     .3248488    .5182161
                {txt}Pr(Ycat=3) |  {res}  .029999       .02021    -.0035238    .0747191
                {txt}Pr(Ycat=4) |  {res} .0396586     .0212918     .0023192    .0826156
                {txt}Pr(Ycat=5) |  {res} .1470236      .046716     .0651913    .2534932
{txt}
{com}. drop b1-b7
{txt}
{com}. 
. 
. *Table B3
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & year>1989), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-399.26925
{txt}Iteration 1:   log pseudolikelihood = {res} -357.4213
{txt}Iteration 2:   log pseudolikelihood = {res}-357.24524
{txt}Iteration 3:   log pseudolikelihood = {res}-357.24516

{txt}Ordered probit estimates                          Number of obs   = {res}       368
                                                  {txt}Wald chi2({res}3{txt})    = {res}     39.77
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-357.24516                 {txt}Pseudo R2       = {res}    0.1053

                               {txt}(Std. Err. adjusted for {res}38{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res}-1.056432   .2211641    -4.78   0.000    -1.489906   -.6229584
      {txt}Ystar3 {c |}  {res}-.7674168    .300459    -2.55   0.011    -1.356306   -.1785279
      {txt}Ystar4 {c |}  {res} .8236184   .4044544     2.04   0.042     .0309023    1.616335
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-.5272474   .5298921          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .8906313   .5311716 
       {txt}_cut3 {c |}  {res} .9726829   .5370295 
       {txt}_cut4 {c |}  {res} 1.279144   .5468297 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 14% 28% 42% 57% 71% 85% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .6782398     .0630349     .5504468      .79623
                {txt}Pr(Ycat=2) |  {res}  .290357      .061024     .1745871    .4121331
                {txt}Pr(Ycat=3) |  {res} .0057524      .004217    -.0005427    .0155696
                {txt}Pr(Ycat=4) |  {res} .0138402     .0074942     .0019728     .031741
                {txt}Pr(Ycat=5) |  {res} .0118106     .0038542      .005796    .0206906
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .2842305     .0574874     .1834198     .405762
                {txt}Pr(Ycat=2) |  {res} .5117736     .0660151     .3746033     .636016
                {txt}Pr(Ycat=3) |  {res} .0215413     .0122678    -.0035876    .0448281
                {txt}Pr(Ycat=4) |  {res} .0691819     .0312679     .0110355    .1349521
                {txt}Pr(Ycat=5) |  {res} .1132728     .0366103     .0513317    .1933855
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .1030121     .0607633     .0245549    .2578046
                {txt}Pr(Ycat=2) |  {res} .4278679     .0883949     .2405878     .596596
                {txt}Pr(Ycat=3) |  {res} .0312001     .0186733    -.0045558    .0666637
                {txt}Pr(Ycat=4) |  {res} .1121032     .0492139     .0169152    .2079998
                {txt}Pr(Ycat=5) |  {res} .3258166     .1125766     .1321915    .5651708
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .3250687     .1789822     .0628588     .713557
                {txt}Pr(Ycat=2) |  {res} .4596718     .0935734      .249154    .6196198
                {txt}Pr(Ycat=3) |  {res}  .020348     .0152692    -.0025345    .0547801
                {txt}Pr(Ycat=4) |  {res} .0653596     .0437523     .0050998    .1676981
                {txt}Pr(Ycat=5) |  {res} .1295519     .1064053     .0078247     .391306
{txt}
{com}. drop b1-b7
{txt}
{com}. 
. 
. *Table B4
. *Model 4
. oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==1), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-475.66904}  
Iteration 1:{space 3}log pseudolikelihood = {res:-468.26245}  
Iteration 2:{space 3}log pseudolikelihood = {res:-468.26105}  
Iteration 3:{space 3}log pseudolikelihood = {res:-468.26105}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       393
{txt}{col 49}Wald chi2({res}3{txt}){col 67}= {res}      8.45
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0375
{txt}Log pseudolikelihood = {res}-468.26105{txt}{col 49}Pseudo R2{col 67}= {res}    0.0156

{txt}{ralign 78:(Std. Err. adjusted for {res:85} clusters in precmid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        Ycat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}Ystar1 {c |}{col 14}{res}{space 2}-.4279756{col 26}{space 2} .3187524{col 37}{space 1}   -1.34{col 46}{space 3}0.179{col 54}{space 4}-1.052719{col 67}{space 3} .1967676
{txt}{space 6}Ystar3 {c |}{col 14}{res}{space 2}-.2412515{col 26}{space 2} .2373702{col 37}{space 1}   -1.02{col 46}{space 3}0.309{col 54}{space 4}-.7064885{col 67}{space 3} .2239854
{txt}{space 6}Ystar4 {c |}{col 14}{res}{space 2} .3655937{col 26}{space 2} .3145384{col 37}{space 1}    1.16{col 46}{space 3}0.245{col 54}{space 4}-.2508902{col 67}{space 3} .9820776
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-.3488606{col 26}{space 2} .3153014{col 54}{space 4}-.9668399{col 67}{space 3} .2691187
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2} .7938511{col 26}{space 2} .2854772{col 54}{space 4}  .234326{col 67}{space 3} 1.353376
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} .8689853{col 26}{space 2}  .253144{col 54}{space 4} .3728322{col 67}{space 3} 1.365138
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} .9904402{col 26}{space 2} .2432065{col 54}{space 4} .5137642{col 67}{space 3} 1.467116
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Model 5
. oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==0), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-466.45508}  
Iteration 1:{space 3}log pseudolikelihood = {res:-436.02642}  
Iteration 2:{space 3}log pseudolikelihood = {res:-435.96199}  
Iteration 3:{space 3}log pseudolikelihood = {res:-435.96198}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       479
{txt}{col 49}Wald chi2({res}3{txt}){col 67}= {res}     54.47
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-435.96198{txt}{col 49}Pseudo R2{col 67}= {res}    0.0654

{txt}{ralign 78:(Std. Err. adjusted for {res:87} clusters in precmid)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        Ycat{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}Ystar1 {c |}{col 14}{res}{space 2}-.7184729{col 26}{space 2} .1789569{col 37}{space 1}   -4.01{col 46}{space 3}0.000{col 54}{space 4}-1.069222{col 67}{space 3}-.3677237
{txt}{space 6}Ystar3 {c |}{col 14}{res}{space 2}-1.328363{col 26}{space 2} .3498094{col 37}{space 1}   -3.80{col 46}{space 3}0.000{col 54}{space 4}-2.013977{col 67}{space 3}-.6427495
{txt}{space 6}Ystar4 {c |}{col 14}{res}{space 2} 1.034272{col 26}{space 2} .4568464{col 37}{space 1}    2.26{col 46}{space 3}0.024{col 54}{space 4} .1388698{col 67}{space 3} 1.929675
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}/cut1 {c |}{col 14}{res}{space 2}-.6160323{col 26}{space 2} .3032191{col 54}{space 4}-1.210331{col 67}{space 3}-.0217337
{txt}{space 7}/cut2 {c |}{col 14}{res}{space 2}  .868886{col 26}{space 2} .3070663{col 54}{space 4} .2670471{col 67}{space 3} 1.470725
{txt}{space 7}/cut3 {c |}{col 14}{res}{space 2} 1.015514{col 26}{space 2} .3121913{col 54}{space 4} .4036306{col 67}{space 3} 1.627398
{txt}{space 7}/cut4 {c |}{col 14}{res}{space 2} 1.530707{col 26}{space 2} .2831897{col 54}{space 4} .9756659{col 67}{space 3} 2.085749
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. *Table 4
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==1), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-475.66904
{txt}Iteration 1:   log pseudolikelihood = {res}-468.26245
{txt}Iteration 2:   log pseudolikelihood = {res}-468.26105

{txt}Ordered probit estimates                          Number of obs   = {res}       393
                                                  {txt}Wald chi2({res}3{txt})    = {res}      8.45
                                                  {txt}Prob > chi2     = {res}    0.0375
{txt}Log pseudolikelihood = {res}-468.26105                 {txt}Pseudo R2       = {res}    0.0156

                               {txt}(Std. Err. adjusted for {res}85{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res}-.4279756   .3187522    -1.34   0.179    -1.052718    .1967673
      {txt}Ystar3 {c |}  {res}-.2412515   .2373701    -1.02   0.309    -.7064884    .2239854
      {txt}Ystar4 {c |}  {res} .3655937   .3145383     1.16   0.245    -.2508901    .9820775
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-.3488606   .3153011          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .7938511   .2854771 
       {txt}_cut3 {c |}  {res} .8689853    .253144 
       {txt}_cut4 {c |}  {res} .9904402   .2432065 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 14% 28% 42% 57% 71% 85% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .4803756     .0627691     .3581465    .6065799
                {txt}Pr(Ycat=2) |  {res} .3759021     .0401742     .2948507    .4555536
                {txt}Pr(Ycat=3) |  {res}  .015512     .0125636    -.0083068    .0415204
                {txt}Pr(Ycat=4) |  {res} .0221469      .008148     .0074301    .0406764
                {txt}Pr(Ycat=5) |  {res} .1060634     .0459832     .0367823    .2162627
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .3239154     .0744396      .195516    .4822575
                {txt}Pr(Ycat=2) |  {res} .4226013     .0500095      .323253    .5184382
                {txt}Pr(Ycat=3) |  {res} .0241136     .0186504    -.0094633    .0632983
                {txt}Pr(Ycat=4) |  {res} .0352089     .0138666     .0093937     .064524
                {txt}Pr(Ycat=5) |  {res} .1941608     .0351419     .1306772    .2640041
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .2461558     .0681667     .1323783    .3879152
                {txt}Pr(Ycat=2) |  {res} .4194169     .0484369     .3253452    .5116664
                {txt}Pr(Ycat=3) |  {res} .0264065     .0200377     -.012242    .0669039
                {txt}Pr(Ycat=4) |  {res} .0408952     .0159584     .0111193    .0733769
                {txt}Pr(Ycat=5) |  {res} .2671255      .065388     .1604014    .4190371
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .3726612     .1150815       .17128    .6070166
                {txt}Pr(Ycat=2) |  {res} .4060528     .0585468     .2864281    .5103771
                {txt}Pr(Ycat=3) |  {res} .0228852     .0186084    -.0063341    .0661984
                {txt}Pr(Ycat=4) |  {res} .0318114     .0145201     .0066881    .0615972
                {txt}Pr(Ycat=5) |  {res} .1665894     .0594846     .0654729    .3003145
{txt}
{com}. drop b1-b7
{txt}
{com}. 
. 
. *Table 5
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==0), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-466.45508
{txt}Iteration 1:   log pseudolikelihood = {res}-436.02642
{txt}Iteration 2:   log pseudolikelihood = {res}-435.96199
{txt}Iteration 3:   log pseudolikelihood = {res}-435.96198

{txt}Ordered probit estimates                          Number of obs   = {res}       479
                                                  {txt}Wald chi2({res}3{txt})    = {res}     54.47
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-435.96198                 {txt}Pseudo R2       = {res}    0.0654

                               {txt}(Std. Err. adjusted for {res}87{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res}-.7184729   .1789569    -4.01   0.000    -1.069222   -.3677238
      {txt}Ystar3 {c |}  {res}-1.328363   .3498094    -3.80   0.000    -2.013977   -.6427496
      {txt}Ystar4 {c |}  {res} 1.034272   .4568464     2.26   0.024     .1388699    1.929675
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res}-.6160324   .3032192          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .8688861   .3070663 
       {txt}_cut3 {c |}  {res} 1.015514   .3121913 
       {txt}_cut4 {c |}  {res} 1.530708   .2831897 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 14% 28% 42% 57% 71% 85% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .6517728     .0501979      .550792    .7505038
                {txt}Pr(Ycat=2) |  {res} .3164017     .0442268     .2295875    .4028708
                {txt}Pr(Ycat=3) |  {res} .0090385      .004664     .0016447    .0194663
                {txt}Pr(Ycat=4) |  {res}  .016413     .0069247      .005539    .0318115
                {txt}Pr(Ycat=5) |  {res} .0063741     .0039111     .0016843    .0170536
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .3761473     .0507613     .2841348    .4804248
                {txt}Pr(Ycat=2) |  {res} .4996868     .0427139     .4156025    .5817164
                {txt}Pr(Ycat=3) |  {res} .0267826     .0111239      .005229    .0499497
                {txt}Pr(Ycat=4) |  {res} .0617263     .0227827     .0216403    .1130174
                {txt}Pr(Ycat=5) |  {res} .0356571     .0138701     .0145927    .0682855
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .0615804     .0436597     .0101674    .1749598
                {txt}Pr(Ycat=2) |  {res} .3809139      .081397     .2000174    .5163929
                {txt}Pr(Ycat=3) |  {res} .0557157     .0238865     .0096844    .1041897
                {txt}Pr(Ycat=4) |  {res} .1901646     .0632453     .0717883    .3204422
                {txt}Pr(Ycat=5) |  {res} .3116254     .1088068     .1271748    .5518585
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .2763585     .1015261     .1130775    .5041142
                {txt}Pr(Ycat=2) |  {res} .5176221     .0478612     .4087434    .6019239
                {txt}Pr(Ycat=3) |  {res} .0374065     .0188289     .0051789    .0766481
                {txt}Pr(Ycat=4) |  {res} .0979628      .050636     .0212585    .2211363
                {txt}Pr(Ycat=5) |  {res} .0706501     .0372877     .0191019    .1634578
{txt}
{com}. drop b1-b7
{txt}
{com}. 
. 
. *Table B5
. oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-767.52686}  
Iteration 1:{space 3}log pseudolikelihood = {res:-701.20521}  
Iteration 2:{space 3}log pseudolikelihood = {res:-700.86209}  
Iteration 3:{space 3}log pseudolikelihood = {res:-700.86208}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       686
{txt}{col 49}Wald chi2({res}13{txt}){col 67}= {res}     84.27
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-700.86208{txt}{col 49}Pseudo R2{col 67}= {res}    0.0869

{txt}{ralign 86:(Std. Err. adjusted for {res:98} clusters in precmid)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                Ycat{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Ystar1 {c |}{col 22}{res}{space 2}-.4848414{col 34}{space 2} .2470665{col 45}{space 1}   -1.96{col 54}{space 3}0.050{col 62}{space 4}-.9690829{col 75}{space 3}-.0005999
{txt}{space 14}Ystar3 {c |}{col 22}{res}{space 2}-.8314399{col 34}{space 2} .2926787{col 45}{space 1}   -2.84{col 54}{space 3}0.005{col 62}{space 4} -1.40508{col 75}{space 3}-.2578002
{txt}{space 14}Ystar4 {c |}{col 22}{res}{space 2} .9001945{col 34}{space 2} .3359751{col 45}{space 1}    2.68{col 54}{space 3}0.007{col 62}{space 4} .2416955{col 75}{space 3} 1.558694
{txt}{space 12}disp_maj {c |}{col 22}{res}{space 2}-.2768103{col 34}{space 2} .1645555{col 45}{space 1}   -1.68{col 54}{space 3}0.093{col 62}{space 4}-.5993331{col 75}{space 3} .0457125
{txt}{space 9}disp_endriv {c |}{col 22}{res}{space 2}-.2602174{col 34}{space 2}  .161389{col 45}{space 1}   -1.61{col 54}{space 3}0.107{col 62}{space 4} -.576534{col 75}{space 3} .0560992
{txt}{space 11}cincratio {c |}{col 22}{res}{space 2}-.1407055{col 34}{space 2} .2288641{col 45}{space 1}   -0.61{col 54}{space 3}0.539{col 62}{space 4}-.5892708{col 75}{space 3} .3078598
{txt}{space 13}hostlev {c |}{col 22}{res}{space 2} .1991746{col 34}{space 2} .1852141{col 45}{space 1}    1.08{col 54}{space 3}0.282{col 62}{space 4}-.1638383{col 75}{space 3} .5621875
{txt}{space 12}fatality {c |}{col 22}{res}{space 2}-.0286276{col 34}{space 2} .0388916{col 45}{space 1}   -0.74{col 54}{space 3}0.462{col 62}{space 4}-.1048538{col 75}{space 3} .0475986
{txt}{space 14}postcw {c |}{col 22}{res}{space 2} .1775439{col 34}{space 2} .1736102{col 45}{space 1}    1.02{col 54}{space 3}0.306{col 62}{space 4}-.1627258{col 75}{space 3} .5178137
{txt}{space 14}igoint {c |}{col 22}{res}{space 2} .5517535{col 34}{space 2} .2117931{col 45}{space 1}    2.61{col 54}{space 3}0.009{col 62}{space 4} .1366467{col 75}{space 3} .9668603
{txt}{space 13}coalint {c |}{col 22}{res}{space 2} .3876785{col 34}{space 2} .2912697{col 45}{space 1}    1.33{col 54}{space 3}0.183{col 62}{space 4}-.1831997{col 75}{space 3} .9585567
{txt}intvmaxpctmembercinc {c |}{col 22}{res}{space 2} .8373654{col 34}{space 2} .3222976{col 45}{space 1}    2.60{col 54}{space 3}0.009{col 62}{space 4} .2056738{col 75}{space 3} 1.469057
{txt}{space 10}intvdempct {c |}{col 22}{res}{space 2} -.319527{col 34}{space 2} .2282801{col 45}{space 1}   -1.40{col 54}{space 3}0.162{col 62}{space 4}-.7669478{col 75}{space 3} .1278938
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}/cut1 {c |}{col 22}{res}{space 2} .7032914{col 34}{space 2} .7539605{col 62}{space 4}-.7744441{col 75}{space 3} 2.181027
{txt}{space 15}/cut2 {c |}{col 22}{res}{space 2} 2.067536{col 34}{space 2} .7291323{col 62}{space 4} .6384634{col 75}{space 3} 3.496609
{txt}{space 15}/cut3 {c |}{col 22}{res}{space 2} 2.179466{col 34}{space 2} .7264324{col 62}{space 4} .7556846{col 75}{space 3} 3.603247
{txt}{space 15}/cut4 {c |}{col 22}{res}{space 2} 2.428464{col 34}{space 2} .7393373{col 62}{space 4}   .97939{col 75}{space 3} 3.877539
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==1), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-383.36346}  
Iteration 1:{space 3}log pseudolikelihood = {res:-362.44928}  
Iteration 2:{space 3}log pseudolikelihood = {res:-362.35627}  
Iteration 3:{space 3}log pseudolikelihood = {res:-362.35626}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       316
{txt}{col 49}Wald chi2({res}13{txt}){col 67}= {res}     55.04
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-362.35626{txt}{col 49}Pseudo R2{col 67}= {res}    0.0548

{txt}{ralign 86:(Std. Err. adjusted for {res:69} clusters in precmid)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                Ycat{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Ystar1 {c |}{col 22}{res}{space 2}-.1404719{col 34}{space 2} .3520926{col 45}{space 1}   -0.40{col 54}{space 3}0.690{col 62}{space 4}-.8305608{col 75}{space 3}  .549617
{txt}{space 14}Ystar3 {c |}{col 22}{res}{space 2}-.5976591{col 34}{space 2} .2938417{col 45}{space 1}   -2.03{col 54}{space 3}0.042{col 62}{space 4}-1.173578{col 75}{space 3}-.0217401
{txt}{space 14}Ystar4 {c |}{col 22}{res}{space 2} .7016171{col 34}{space 2} .3755295{col 45}{space 1}    1.87{col 54}{space 3}0.062{col 62}{space 4}-.0344073{col 75}{space 3} 1.437641
{txt}{space 12}disp_maj {c |}{col 22}{res}{space 2}-.3085261{col 34}{space 2} .2550433{col 45}{space 1}   -1.21{col 54}{space 3}0.226{col 62}{space 4}-.8084018{col 75}{space 3} .1913497
{txt}{space 9}disp_endriv {c |}{col 22}{res}{space 2}-.0831863{col 34}{space 2} .2357817{col 45}{space 1}   -0.35{col 54}{space 3}0.724{col 62}{space 4}  -.54531{col 75}{space 3} .3789374
{txt}{space 11}cincratio {c |}{col 22}{res}{space 2}-.0216284{col 34}{space 2} .3278977{col 45}{space 1}   -0.07{col 54}{space 3}0.947{col 62}{space 4}-.6642961{col 75}{space 3} .6210392
{txt}{space 13}hostlev {c |}{col 22}{res}{space 2}-.1802036{col 34}{space 2} .2356724{col 45}{space 1}   -0.76{col 54}{space 3}0.444{col 62}{space 4}-.6421129{col 75}{space 3} .2817058
{txt}{space 12}fatality {c |}{col 22}{res}{space 2} .0406418{col 34}{space 2} .0516221{col 45}{space 1}    0.79{col 54}{space 3}0.431{col 62}{space 4}-.0605357{col 75}{space 3} .1418193
{txt}{space 14}postcw {c |}{col 22}{res}{space 2} .1793978{col 34}{space 2} .2119542{col 45}{space 1}    0.85{col 54}{space 3}0.397{col 62}{space 4}-.2360248{col 75}{space 3} .5948204
{txt}{space 14}igoint {c |}{col 22}{res}{space 2} .4288736{col 34}{space 2} .2628398{col 45}{space 1}    1.63{col 54}{space 3}0.103{col 62}{space 4} -.086283{col 75}{space 3} .9440302
{txt}{space 13}coalint {c |}{col 22}{res}{space 2} .3226332{col 34}{space 2} .3896067{col 45}{space 1}    0.83{col 54}{space 3}0.408{col 62}{space 4}-.4409819{col 75}{space 3} 1.086248
{txt}intvmaxpctmembercinc {c |}{col 22}{res}{space 2} .9312887{col 34}{space 2} .3985779{col 45}{space 1}    2.34{col 54}{space 3}0.019{col 62}{space 4} .1500903{col 75}{space 3} 1.712487
{txt}{space 10}intvdempct {c |}{col 22}{res}{space 2}-.6019727{col 34}{space 2}  .249327{col 45}{space 1}   -2.41{col 54}{space 3}0.016{col 62}{space 4}-1.090645{col 75}{space 3}-.1133008
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}/cut1 {c |}{col 22}{res}{space 2} -.647189{col 34}{space 2} .9558155{col 62}{space 4}-2.520553{col 75}{space 3} 1.226175
{txt}{space 15}/cut2 {c |}{col 22}{res}{space 2} .6096749{col 34}{space 2} .9753435{col 62}{space 4}-1.301963{col 75}{space 3} 2.521313
{txt}{space 15}/cut3 {c |}{col 22}{res}{space 2} .7100517{col 34}{space 2} .9383962{col 62}{space 4}-1.129171{col 75}{space 3} 2.549274
{txt}{space 15}/cut4 {c |}{col 22}{res}{space 2} .8632377{col 34}{space 2} .9375706{col 62}{space 4} -.974367{col 75}{space 3} 2.700842
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc  intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==0), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-362.89417}  
Iteration 1:{space 3}log pseudolikelihood = {res:-307.76035}  
Iteration 2:{space 3}log pseudolikelihood = {res:-307.32106}  
Iteration 3:{space 3}log pseudolikelihood = {res:-307.32071}  
Iteration 4:{space 3}log pseudolikelihood = {res:-307.32071}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       370
{txt}{col 49}Wald chi2({res}13{txt}){col 67}= {res}     67.68
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-307.32071{txt}{col 49}Pseudo R2{col 67}= {res}    0.1531

{txt}{ralign 86:(Std. Err. adjusted for {res:70} clusters in precmid)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                Ycat{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Ystar1 {c |}{col 22}{res}{space 2}-.7665147{col 34}{space 2} .2036056{col 45}{space 1}   -3.76{col 54}{space 3}0.000{col 62}{space 4}-1.165574{col 75}{space 3}-.3674551
{txt}{space 14}Ystar3 {c |}{col 22}{res}{space 2}-1.920623{col 34}{space 2} .5309699{col 45}{space 1}   -3.62{col 54}{space 3}0.000{col 62}{space 4}-2.961305{col 75}{space 3}-.8799412
{txt}{space 14}Ystar4 {c |}{col 22}{res}{space 2} 1.811637{col 34}{space 2} .5929782{col 45}{space 1}    3.06{col 54}{space 3}0.002{col 62}{space 4} .6494216{col 75}{space 3} 2.973853
{txt}{space 12}disp_maj {c |}{col 22}{res}{space 2}-.1225065{col 34}{space 2}  .307223{col 45}{space 1}   -0.40{col 54}{space 3}0.690{col 62}{space 4}-.7246525{col 75}{space 3} .4796396
{txt}{space 9}disp_endriv {c |}{col 22}{res}{space 2}-.5076916{col 34}{space 2}  .262921{col 45}{space 1}   -1.93{col 54}{space 3}0.053{col 62}{space 4}-1.023007{col 75}{space 3} .0076241
{txt}{space 11}cincratio {c |}{col 22}{res}{space 2}-.1124393{col 34}{space 2}  .429338{col 45}{space 1}   -0.26{col 54}{space 3}0.793{col 62}{space 4}-.9539262{col 75}{space 3} .7290477
{txt}{space 13}hostlev {c |}{col 22}{res}{space 2} .7938142{col 34}{space 2} .3193241{col 45}{space 1}    2.49{col 54}{space 3}0.013{col 62}{space 4} .1679505{col 75}{space 3} 1.419678
{txt}{space 12}fatality {c |}{col 22}{res}{space 2}-.1140539{col 34}{space 2} .0659944{col 45}{space 1}   -1.73{col 54}{space 3}0.084{col 62}{space 4}-.2434005{col 75}{space 3} .0152927
{txt}{space 14}postcw {c |}{col 22}{res}{space 2} .2874416{col 34}{space 2} .2474995{col 45}{space 1}    1.16{col 54}{space 3}0.245{col 62}{space 4}-.1976485{col 75}{space 3} .7725317
{txt}{space 14}igoint {c |}{col 22}{res}{space 2} .5699443{col 34}{space 2} .2459242{col 45}{space 1}    2.32{col 54}{space 3}0.020{col 62}{space 4} .0879417{col 75}{space 3} 1.051947
{txt}{space 13}coalint {c |}{col 22}{res}{space 2} .1414775{col 34}{space 2} .6361306{col 45}{space 1}    0.22{col 54}{space 3}0.824{col 62}{space 4}-1.105316{col 75}{space 3} 1.388271
{txt}intvmaxpctmembercinc {c |}{col 22}{res}{space 2} 1.039054{col 34}{space 2} .7595605{col 45}{space 1}    1.37{col 54}{space 3}0.171{col 62}{space 4}-.4496574{col 75}{space 3} 2.527765
{txt}{space 10}intvdempct {c |}{col 22}{res}{space 2}-.3222377{col 34}{space 2}  .268235{col 45}{space 1}   -1.20{col 54}{space 3}0.230{col 62}{space 4}-.8479686{col 75}{space 3} .2034932
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}/cut1 {c |}{col 22}{res}{space 2} 2.709369{col 34}{space 2} 1.279852{col 62}{space 4} .2009063{col 75}{space 3} 5.217833
{txt}{space 15}/cut2 {c |}{col 22}{res}{space 2} 4.356398{col 34}{space 2} 1.246618{col 62}{space 4} 1.913071{col 75}{space 3} 6.799725
{txt}{space 15}/cut3 {c |}{col 22}{res}{space 2} 4.505702{col 34}{space 2} 1.250025{col 62}{space 4} 2.055697{col 75}{space 3} 6.955706
{txt}{space 15}/cut4 {c |}{col 22}{res}{space 2} 5.069475{col 34}{space 2} 1.278587{col 62}{space 4} 2.563491{col 75}{space 3} 7.575459
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. *Table B6
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc  intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-767.52686
{txt}Iteration 1:   log pseudolikelihood = {res}-701.30147
{txt}Iteration 2:   log pseudolikelihood = {res}-700.86221
{txt}Iteration 3:   log pseudolikelihood = {res}-700.86208

{txt}Ordered probit estimates                          Number of obs   = {res}       686
                                                  {txt}Wald chi2({res}13{txt})   = {res}     84.27
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-700.86208                 {txt}Pseudo R2       = {res}    0.0869

                               {txt}(Std. Err. adjusted for {res}98{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res}-.4848414   .2470665    -1.96   0.050    -.9690828   -.0005999
      {txt}Ystar3 {c |}  {res}  -.83144   .2926787    -2.84   0.005     -1.40508   -.2578003
      {txt}Ystar4 {c |}  {res} .9001946   .3359751     2.68   0.007     .2416955    1.558694
    {txt}disp_maj {c |}  {res}-.2768103   .1645555    -1.68   0.093    -.5993331    .0457124
 {txt}disp_endriv {c |}  {res}-.2602174    .161389    -1.61   0.107     -.576534    .0560991
   {txt}cincratio {c |}  {res}-.1407055    .228864    -0.61   0.539    -.5892708    .3078598
     {txt}hostlev {c |}  {res} .1991746   .1852141     1.08   0.282    -.1638383    .5621875
    {txt}fatality {c |}  {res}-.0286276   .0388916    -0.74   0.462    -.1048538    .0475986
      {txt}postcw {c |}  {res} .1775439   .1736102     1.02   0.306    -.1627258    .5178136
      {txt}igoint {c |}  {res} .5517535   .2117931     2.61   0.009     .1366468    .9668603
     {txt}coalint {c |}  {res} .3876785   .2912697     1.33   0.183    -.1831997    .9585567
{txt}intvmaxpct~c {c |}  {res} .8373654   .3222976     2.60   0.009     .2056738    1.469057
  {txt}intvdempct {c |}  {res} -.319527   .2282801    -1.40   0.162    -.7669478    .1278938
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} .7032914   .7539605          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} 2.067537   .7291323 
       {txt}_cut3 {c |}  {res} 2.179466   .7264324 
       {txt}_cut4 {c |}  {res} 2.428464   .7393372 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 5% 11% 17% 23% 29% 35% 41% 47% 52% 58% 64% 70% 76% 82% 88% 94% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 b15 b16 b17
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .6705914     .0834763     .4970376    .8231991
                {txt}Pr(Ycat=2) |  {res} .2901528      .067194      .162981     .425966
                {txt}Pr(Ycat=3) |  {res} .0077131     .0046872     .0008035    .0190403
                {txt}Pr(Ycat=4) |  {res} .0124034      .006255     .0031418    .0269829
                {txt}Pr(Ycat=5) |  {res} .0191392     .0151895       .00258    .0587745
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .4913419      .100486     .2992881    .6913325
                {txt}Pr(Ycat=2) |  {res}  .414132     .0752988     .2608095    .5564361
                {txt}Pr(Ycat=3) |  {res} .0170206     .0095783     .0016419    .0383781
                {txt}Pr(Ycat=4) |  {res} .0296039     .0136863     .0068554    .0600139
                {txt}Pr(Ycat=5) |  {res} .0479017     .0192424     .0199134    .0926518
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .2133106     .0985775     .0570749    .4436905
                {txt}Pr(Ycat=2) |  {res} .4745788     .0525643     .3621158    .5698083
                {txt}Pr(Ycat=3) |  {res} .0364563     .0191534     .0039117    .0747341
                {txt}Pr(Ycat=4) |  {res} .0710272     .0274012     .0214073    .1251302
                {txt}Pr(Ycat=5) |  {res} .2046271     .0981964     .0638823    .4435617
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .5184078     .1402746     .2435468    .7946551
                {txt}Pr(Ycat=2) |  {res} .3916017     .0966814     .1854424    .5613325
                {txt}Pr(Ycat=3) |  {res} .0173425     .0129832     .0009986    .0488012
                {txt}Pr(Ycat=4) |  {res} .0273445     .0160045     .0046167    .0637692
                {txt}Pr(Ycat=5) |  {res} .0453034     .0290516     .0088929    .1173546
{txt}
{com}. drop b1-b17
{txt}
{com}. 
. *Table B7
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc  intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==1), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-383.36346
{txt}Iteration 1:   log pseudolikelihood = {res}-362.44928
{txt}Iteration 2:   log pseudolikelihood = {res}-362.35627
{txt}Iteration 3:   log pseudolikelihood = {res}-362.35626

{txt}Ordered probit estimates                          Number of obs   = {res}       316
                                                  {txt}Wald chi2({res}13{txt})   = {res}     55.04
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-362.35626                 {txt}Pseudo R2       = {res}    0.0548

                               {txt}(Std. Err. adjusted for {res}69{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res}-.1404719   .3520927    -0.40   0.690    -.8305608     .549617
      {txt}Ystar3 {c |}  {res}-.5976592   .2938417    -2.03   0.042    -1.173578   -.0217401
      {txt}Ystar4 {c |}  {res} .7016171   .3755296     1.87   0.062    -.0344073    1.437641
    {txt}disp_maj {c |}  {res}-.3085261   .2550433    -1.21   0.226    -.8084018    .1913497
 {txt}disp_endriv {c |}  {res}-.0831863   .2357817    -0.35   0.724      -.54531    .3789374
   {txt}cincratio {c |}  {res}-.0216285   .3278977    -0.07   0.947    -.6642962    .6210392
     {txt}hostlev {c |}  {res}-.1802036   .2356724    -0.76   0.444    -.6421129    .2817058
    {txt}fatality {c |}  {res} .0406418   .0516221     0.79   0.431    -.0605357    .1418193
      {txt}postcw {c |}  {res} .1793978   .2119542     0.85   0.397    -.2360248    .5948204
      {txt}igoint {c |}  {res} .4288736   .2628398     1.63   0.103     -.086283    .9440303
     {txt}coalint {c |}  {res} .3226332   .3896067     0.83   0.408    -.4409818    1.086248
{txt}intvmaxpct~c {c |}  {res} .9312887   .3985779     2.34   0.019     .1500903    1.712487
  {txt}intvdempct {c |}  {res}-.6019727    .249327    -2.41   0.016    -1.090645   -.1133008
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} -.647189   .9558155          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} .6096749   .9753435 
       {txt}_cut3 {c |}  {res} .7100517   .9383962 
       {txt}_cut4 {c |}  {res} .8632377   .9375707 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 5% 11% 17% 23% 29% 35% 41% 47% 52% 58% 64% 70% 76% 82% 88% 94% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 b15 b16 b17
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .5464816     .1118769     .3337449    .7605741
                {txt}Pr(Ycat=2) |  {res}   .35872     .0724469     .2133096    .4906365
                {txt}Pr(Ycat=3) |  {res} .0129764     .0120463    -.0106684    .0415827
                {txt}Pr(Ycat=4) |  {res} .0176334     .0085873     .0038834    .0372778
                {txt}Pr(Ycat=5) |  {res} .0641886     .0458967     .0086507    .1776136
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .4975887     .1201188      .274597    .7340764
                {txt}Pr(Ycat=2) |  {res}  .388769     .0810151     .2154942    .5355873
                {txt}Pr(Ycat=3) |  {res} .0171358     .0147965    -.0085834    .0480512
                {txt}Pr(Ycat=4) |  {res} .0230794     .0126737     .0040925    .0520262
                {txt}Pr(Ycat=5) |  {res} .0734272     .0347163     .0231292    .1592802
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .2859207       .10888     .1027794    .5234922
                {txt}Pr(Ycat=2) |  {res} .4479381     .0532639     .3283462    .5470422
                {txt}Pr(Ycat=3) |  {res} .0293825     .0241285      -.01611    .0766478
                {txt}Pr(Ycat=4) |  {res} .0416621     .0190325     .0084354    .0806921
                {txt}Pr(Ycat=5) |  {res} .1950966     .0910219     .0609541    .4019298
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .5357921     .1615148     .2273391    .8498119
                {txt}Pr(Ycat=2) |  {res} .3597543      .103233     .1314202    .5273069
                {txt}Pr(Ycat=3) |  {res} .0171805     .0167479    -.0055383    .0568529
                {txt}Pr(Ycat=4) |  {res} .0208637       .01427     .0021509    .0566129
                {txt}Pr(Ycat=5) |  {res} .0664094     .0470919     .0093356    .1942418
{txt}
{com}. drop b1-b17
{txt}
{com}. 
. *Table B8
. set seed 8675309
{txt}
{com}. estsimp oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc  intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & lagstsuccess==0), cluster(precmid)

{txt}Iteration 0:   log pseudolikelihood = {res}-362.89417
{txt}Iteration 1:   log pseudolikelihood = {res} -308.3011
{txt}Iteration 2:   log pseudolikelihood = {res}-307.32316
{txt}Iteration 3:   log pseudolikelihood = {res}-307.32071

{txt}Ordered probit estimates                          Number of obs   = {res}       370
                                                  {txt}Wald chi2({res}13{txt})   = {res}     67.68
                                                  {txt}Prob > chi2     = {res}    0.0000
{txt}Log pseudolikelihood = {res}-307.32071                 {txt}Pseudo R2       = {res}    0.1531

                               {txt}(Std. Err. adjusted for {res}70{txt} clusters in precmid)
{hline 13}{c TT}{hline 64}
             {c |}               Robust
        Ycat {c |}      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
{hline 13}{c +}{hline 64}
      Ystar1 {c |}  {res}-.7665147   .2036045    -3.76   0.000    -1.165572   -.3674572
      {txt}Ystar3 {c |}  {res}-1.920623   .5309688    -3.62   0.000    -2.961303   -.8799434
      {txt}Ystar4 {c |}  {res} 1.811637   .5929763     3.06   0.002     .6494252     2.97385
    {txt}disp_maj {c |}  {res}-.1225065   .3072221    -0.40   0.690    -.7246506    .4796377
 {txt}disp_endriv {c |}  {res}-.5076916     .26292    -1.93   0.053    -1.023005     .007622
   {txt}cincratio {c |}  {res}-.1124393   .4293363    -0.26   0.793     -.953923    .7290445
     {txt}hostlev {c |}  {res} .7938142   .3193228     2.49   0.013     .1679531    1.419675
    {txt}fatality {c |}  {res}-.1140539   .0659941    -1.73   0.084       -.2434    .0152922
      {txt}postcw {c |}  {res} .2874416   .2474986     1.16   0.245    -.1976467      .77253
      {txt}igoint {c |}  {res} .5699443   .2459234     2.32   0.020     .0879432    1.051945
     {txt}coalint {c |}  {res} .1414775   .6361291     0.22   0.824    -1.105313    1.388268
{txt}intvmaxpct~c {c |}  {res} 1.039054   .7595578     1.37   0.171    -.4496521     2.52776
  {txt}intvdempct {c |}  {res}-.3222377   .2682339    -1.20   0.230    -.8479664     .203491
{txt}{hline 13}{c +}{hline 64}
       _cut1 {c |}  {res} 2.709369   1.279847          {txt}(Ancillary parameters)
       _cut2 {c |}  {res} 4.356398   1.246614 
       {txt}_cut3 {c |}  {res} 4.505702   1.250021 
       {txt}_cut4 {c |}  {res} 5.069475   1.278583 
{txt}{hline 13}{c BT}{hline 64}

{res}Simulating main parameters.  Please wait....
% of simulations completed: 5% 11% 17% 23% 29% 35% 41% 47% 52% 58% 64% 70% 76% 82% 88% 94% 100% 

Number of simulations  : 1000
Names of new variables : b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12 b13 b14 b15 b16 b17
{txt}
{com}. setx Ystar1 1 Ystar3 1 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .7227387     .0954272     .5146935    .8841393
                {txt}Pr(Ycat=2) |  {res} .2619124     .0857876      .110977    .4414864
                {txt}Pr(Ycat=3) |  {res} .0047746     .0041027      .000225    .0162922
                {txt}Pr(Ycat=4) |  {res} .0077443     .0056352     .0011211    .0221304
                {txt}Pr(Ycat=5) |  {res}   .00283      .004011     .0000915     .012663
{txt}
{com}. setx Ystar1 0 Ystar3 1 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .4456543     .1190867      .230316     .680054
                {txt}Pr(Ycat=2) |  {res} .4791984     .0875875     .2977144    .6280787
                {txt}Pr(Ycat=3) |  {res} .0179173     .0112935     .0013122    .0455891
                {txt}Pr(Ycat=4) |  {res}  .038992     .0227878     .0086493    .0903357
                {txt}Pr(Ycat=5) |  {res}  .018238     .0155996     .0019621    .0611333
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 1 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .0383581      .051664     .0006171    .1898449
                {txt}Pr(Ycat=2) |  {res} .3219373     .1306382     .0721127    .5478291
                {txt}Pr(Ycat=3) |  {res} .0500569     .0251971     .0040832    .1017959
                {txt}Pr(Ycat=4) |  {res} .1987872     .0736119     .0583903    .3425256
                {txt}Pr(Ycat=5) |  {res} .3908605     .1780117     .0956011    .7715776
{txt}
{com}. setx Ystar1 0 Ystar3 0 Ystar4 0 disp_maj mean disp_endriv 0 cincratio mean hostlev mean fatality mean postcw 0 igoint 0 coalint 0 intvmaxpctmembercinc mean intvdempct mean
{txt}
{com}. simqi

{txt}      Quantity of Interest |     Mean       Std. Err.    [95% Conf. Interval]
---------------------------+--------------------------------------------------
                Pr(Ycat=1) |  {res} .4029026     .1304507     .1670928    .6597706
                {txt}Pr(Ycat=2) |  {res} .4997853     .0836795     .3150866    .6289453
                {txt}Pr(Ycat=3) |  {res} .0220908     .0153731     .0018723    .0585619
                {txt}Pr(Ycat=4) |  {res} .0483306     .0295372     .0087849    .1242277
                {txt}Pr(Ycat=5) |  {res} .0268907     .0269643     .0018645    .1051506
{txt}
{com}. drop b1-b17
{txt}
{com}. 
. 
. ***************************************************
. 
. *Model Fit, Appendix C
. *Likelihood Ratio Test
. *Notes: (i) Clustering/robust standard errors are not possible; (ii) Both versions must have same number of observations, so force m1 into observations where the Ystar variables exist.
. oprobit Ycat disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258 & Ystar1!=. & Ystar3!=. & Ystar4!=.)

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-767.52686}  
Iteration 1:{space 3}log likelihood = {res:-724.24716}  
Iteration 2:{space 3}log likelihood = {res:-724.09567}  
Iteration 3:{space 3}log likelihood = {res:-724.09566}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       686
{txt}{col 49}LR chi2({res}10{txt}){col 67}= {res}     86.86
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-724.09566{txt}{col 49}Pseudo R2{col 67}= {res}    0.0566

{txt}{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                Ycat{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}disp_maj {c |}{col 22}{res}{space 2}-.4054815{col 34}{space 2} .1389103{col 45}{space 1}   -2.92{col 54}{space 3}0.004{col 62}{space 4}-.6777407{col 75}{space 3}-.1332223
{txt}{space 9}disp_endriv {c |}{col 22}{res}{space 2}-.3445297{col 34}{space 2} .1117474{col 45}{space 1}   -3.08{col 54}{space 3}0.002{col 62}{space 4}-.5635505{col 75}{space 3}-.1255089
{txt}{space 11}cincratio {c |}{col 22}{res}{space 2}-.0688616{col 34}{space 2} .2047348{col 45}{space 1}   -0.34{col 54}{space 3}0.737{col 62}{space 4}-.4701344{col 75}{space 3} .3324112
{txt}{space 13}hostlev {c |}{col 22}{res}{space 2}  .323309{col 34}{space 2} .1556336{col 45}{space 1}    2.08{col 54}{space 3}0.038{col 62}{space 4} .0182728{col 75}{space 3} .6283451
{txt}{space 12}fatality {c |}{col 22}{res}{space 2}-.0427825{col 34}{space 2} .0338518{col 45}{space 1}   -1.26{col 54}{space 3}0.206{col 62}{space 4}-.1091308{col 75}{space 3} .0235659
{txt}{space 14}postcw {c |}{col 22}{res}{space 2} .2114365{col 34}{space 2}  .114238{col 45}{space 1}    1.85{col 54}{space 3}0.064{col 62}{space 4}-.0124657{col 75}{space 3} .4353388
{txt}{space 14}igoint {c |}{col 22}{res}{space 2} .5012084{col 34}{space 2} .1253938{col 45}{space 1}    4.00{col 54}{space 3}0.000{col 62}{space 4} .2554411{col 75}{space 3} .7469757
{txt}{space 13}coalint {c |}{col 22}{res}{space 2} .2836344{col 34}{space 2} .3347093{col 45}{space 1}    0.85{col 54}{space 3}0.397{col 62}{space 4}-.3723837{col 75}{space 3} .9396526
{txt}intvmaxpctmembercinc {c |}{col 22}{res}{space 2} .8062196{col 34}{space 2} .3387798{col 45}{space 1}    2.38{col 54}{space 3}0.017{col 62}{space 4} .1422233{col 75}{space 3} 1.470216
{txt}{space 10}intvdempct {c |}{col 22}{res}{space 2}-.2551375{col 34}{space 2} .1336667{col 45}{space 1}   -1.91{col 54}{space 3}0.056{col 62}{space 4}-.5171195{col 75}{space 3} .0068444
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}/cut1 {c |}{col 22}{res}{space 2} 1.290719{col 34}{space 2} .5854653{col 62}{space 4} .1432281{col 75}{space 3}  2.43821
{txt}{space 15}/cut2 {c |}{col 22}{res}{space 2} 2.582527{col 34}{space 2}  .590026{col 62}{space 4} 1.426097{col 75}{space 3} 3.738956
{txt}{space 15}/cut3 {c |}{col 22}{res}{space 2} 2.687914{col 34}{space 2} .5906277{col 62}{space 4} 1.530305{col 75}{space 3} 3.845523
{txt}{space 15}/cut4 {c |}{col 22}{res}{space 2} 2.931249{col 34}{space 2} .5922245{col 62}{space 4} 1.770511{col 75}{space 3} 4.091988
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store m1
{txt}
{com}. oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258)

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-767.52686}  
Iteration 1:{space 3}log likelihood = {res:-701.20521}  
Iteration 2:{space 3}log likelihood = {res:-700.86209}  
Iteration 3:{space 3}log likelihood = {res:-700.86208}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       686
{txt}{col 49}LR chi2({res}13{txt}){col 67}= {res}    133.33
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-700.86208{txt}{col 49}Pseudo R2{col 67}= {res}    0.0869

{txt}{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}                Ycat{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Ystar1 {c |}{col 22}{res}{space 2}-.4848414{col 34}{space 2} .0993844{col 45}{space 1}   -4.88{col 54}{space 3}0.000{col 62}{space 4}-.6796311{col 75}{space 3}-.2900516
{txt}{space 14}Ystar3 {c |}{col 22}{res}{space 2}-.8314399{col 34}{space 2} .2335465{col 45}{space 1}   -3.56{col 54}{space 3}0.000{col 62}{space 4}-1.289183{col 75}{space 3}-.3736972
{txt}{space 14}Ystar4 {c |}{col 22}{res}{space 2} .9001945{col 34}{space 2} .2683916{col 45}{space 1}    3.35{col 54}{space 3}0.001{col 62}{space 4} .3741567{col 75}{space 3} 1.426232
{txt}{space 12}disp_maj {c |}{col 22}{res}{space 2}-.2768103{col 34}{space 2} .1422206{col 45}{space 1}   -1.95{col 54}{space 3}0.052{col 62}{space 4}-.5555575{col 75}{space 3} .0019368
{txt}{space 9}disp_endriv {c |}{col 22}{res}{space 2}-.2602174{col 34}{space 2} .1150007{col 45}{space 1}   -2.26{col 54}{space 3}0.024{col 62}{space 4}-.4856146{col 75}{space 3}-.0348203
{txt}{space 11}cincratio {c |}{col 22}{res}{space 2}-.1407055{col 34}{space 2} .2077116{col 45}{space 1}   -0.68{col 54}{space 3}0.498{col 62}{space 4}-.5478127{col 75}{space 3} .2664017
{txt}{space 13}hostlev {c |}{col 22}{res}{space 2} .1991746{col 34}{space 2} .1586092{col 45}{space 1}    1.26{col 54}{space 3}0.209{col 62}{space 4}-.1116937{col 75}{space 3} .5100429
{txt}{space 12}fatality {c |}{col 22}{res}{space 2}-.0286276{col 34}{space 2} .0343985{col 45}{space 1}   -0.83{col 54}{space 3}0.405{col 62}{space 4}-.0960474{col 75}{space 3} .0387922
{txt}{space 14}postcw {c |}{col 22}{res}{space 2} .1775439{col 34}{space 2} .1157574{col 45}{space 1}    1.53{col 54}{space 3}0.125{col 62}{space 4}-.0493364{col 75}{space 3} .4044243
{txt}{space 14}igoint {c |}{col 22}{res}{space 2} .5517535{col 34}{space 2} .1279519{col 45}{space 1}    4.31{col 54}{space 3}0.000{col 62}{space 4} .3009725{col 75}{space 3} .8025346
{txt}{space 13}coalint {c |}{col 22}{res}{space 2} .3876785{col 34}{space 2} .3384038{col 45}{space 1}    1.15{col 54}{space 3}0.252{col 62}{space 4}-.2755807{col 75}{space 3} 1.050938
{txt}intvmaxpctmembercinc {c |}{col 22}{res}{space 2} .8373654{col 34}{space 2}  .342711{col 45}{space 1}    2.44{col 54}{space 3}0.015{col 62}{space 4} .1656642{col 75}{space 3} 1.509067
{txt}{space 10}intvdempct {c |}{col 22}{res}{space 2} -.319527{col 34}{space 2} .1360716{col 45}{space 1}   -2.35{col 54}{space 3}0.019{col 62}{space 4}-.5862224{col 75}{space 3}-.0528315
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}/cut1 {c |}{col 22}{res}{space 2} .7032914{col 34}{space 2} .6080066{col 62}{space 4}-.4883797{col 75}{space 3} 1.894962
{txt}{space 15}/cut2 {c |}{col 22}{res}{space 2} 2.067536{col 34}{space 2} .6107921{col 62}{space 4}  .870406{col 75}{space 3} 3.264667
{txt}{space 15}/cut3 {c |}{col 22}{res}{space 2} 2.179466{col 34}{space 2} .6113386{col 62}{space 4} .9812643{col 75}{space 3} 3.377668
{txt}{space 15}/cut4 {c |}{col 22}{res}{space 2} 2.428464{col 34}{space 2} .6130028{col 62}{space 4} 1.227001{col 75}{space 3} 3.629928
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estimates store m2
{txt}
{com}. lrtest m1 m2

{txt}Likelihood-ratio test{col 55}LR chi2({res}3{txt}){col 67}={res}     46.47
{txt}(Assumption: {res}{stata est replay m1:m1}{txt} nested in {res}{stata est replay m2:m2}{txt}){col 55}Prob > chi2 = {res}   0.0000
{txt}
{com}. 
. *Wald test
. oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-767.52686}  
Iteration 1:{space 3}log pseudolikelihood = {res:-701.20521}  
Iteration 2:{space 3}log pseudolikelihood = {res:-700.86209}  
Iteration 3:{space 3}log pseudolikelihood = {res:-700.86208}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       686
{txt}{col 49}Wald chi2({res}13{txt}){col 67}= {res}     84.27
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-700.86208{txt}{col 49}Pseudo R2{col 67}= {res}    0.0869

{txt}{ralign 86:(Std. Err. adjusted for {res:98} clusters in precmid)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                Ycat{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Ystar1 {c |}{col 22}{res}{space 2}-.4848414{col 34}{space 2} .2470665{col 45}{space 1}   -1.96{col 54}{space 3}0.050{col 62}{space 4}-.9690829{col 75}{space 3}-.0005999
{txt}{space 14}Ystar3 {c |}{col 22}{res}{space 2}-.8314399{col 34}{space 2} .2926787{col 45}{space 1}   -2.84{col 54}{space 3}0.005{col 62}{space 4} -1.40508{col 75}{space 3}-.2578002
{txt}{space 14}Ystar4 {c |}{col 22}{res}{space 2} .9001945{col 34}{space 2} .3359751{col 45}{space 1}    2.68{col 54}{space 3}0.007{col 62}{space 4} .2416955{col 75}{space 3} 1.558694
{txt}{space 12}disp_maj {c |}{col 22}{res}{space 2}-.2768103{col 34}{space 2} .1645555{col 45}{space 1}   -1.68{col 54}{space 3}0.093{col 62}{space 4}-.5993331{col 75}{space 3} .0457125
{txt}{space 9}disp_endriv {c |}{col 22}{res}{space 2}-.2602174{col 34}{space 2}  .161389{col 45}{space 1}   -1.61{col 54}{space 3}0.107{col 62}{space 4} -.576534{col 75}{space 3} .0560992
{txt}{space 11}cincratio {c |}{col 22}{res}{space 2}-.1407055{col 34}{space 2} .2288641{col 45}{space 1}   -0.61{col 54}{space 3}0.539{col 62}{space 4}-.5892708{col 75}{space 3} .3078598
{txt}{space 13}hostlev {c |}{col 22}{res}{space 2} .1991746{col 34}{space 2} .1852141{col 45}{space 1}    1.08{col 54}{space 3}0.282{col 62}{space 4}-.1638383{col 75}{space 3} .5621875
{txt}{space 12}fatality {c |}{col 22}{res}{space 2}-.0286276{col 34}{space 2} .0388916{col 45}{space 1}   -0.74{col 54}{space 3}0.462{col 62}{space 4}-.1048538{col 75}{space 3} .0475986
{txt}{space 14}postcw {c |}{col 22}{res}{space 2} .1775439{col 34}{space 2} .1736102{col 45}{space 1}    1.02{col 54}{space 3}0.306{col 62}{space 4}-.1627258{col 75}{space 3} .5178137
{txt}{space 14}igoint {c |}{col 22}{res}{space 2} .5517535{col 34}{space 2} .2117931{col 45}{space 1}    2.61{col 54}{space 3}0.009{col 62}{space 4} .1366467{col 75}{space 3} .9668603
{txt}{space 13}coalint {c |}{col 22}{res}{space 2} .3876785{col 34}{space 2} .2912697{col 45}{space 1}    1.33{col 54}{space 3}0.183{col 62}{space 4}-.1831997{col 75}{space 3} .9585567
{txt}intvmaxpctmembercinc {c |}{col 22}{res}{space 2} .8373654{col 34}{space 2} .3222976{col 45}{space 1}    2.60{col 54}{space 3}0.009{col 62}{space 4} .2056738{col 75}{space 3} 1.469057
{txt}{space 10}intvdempct {c |}{col 22}{res}{space 2} -.319527{col 34}{space 2} .2282801{col 45}{space 1}   -1.40{col 54}{space 3}0.162{col 62}{space 4}-.7669478{col 75}{space 3} .1278938
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}/cut1 {c |}{col 22}{res}{space 2} .7032914{col 34}{space 2} .7539605{col 62}{space 4}-.7744441{col 75}{space 3} 2.181027
{txt}{space 15}/cut2 {c |}{col 22}{res}{space 2} 2.067536{col 34}{space 2} .7291323{col 62}{space 4} .6384634{col 75}{space 3} 3.496609
{txt}{space 15}/cut3 {c |}{col 22}{res}{space 2} 2.179466{col 34}{space 2} .7264324{col 62}{space 4} .7556846{col 75}{space 3} 3.603247
{txt}{space 15}/cut4 {c |}{col 22}{res}{space 2} 2.428464{col 34}{space 2} .7393373{col 62}{space 4}   .97939{col 75}{space 3} 3.877539
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test Ystar1 Ystar3 Ystar4

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[Ycat]Ystar1 = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [Ycat]Ystar3 = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [Ycat]Ystar4 = 0{p_end}

{txt}{col 12}chi2(  3) ={res}   22.06
{txt}{col 10}Prob > chi2 =  {res}  0.0001
{txt}
{com}. 
. *Out-of-Sample Predictions
. *Notes: (i) Removed outliers from list of MIDs under foreach commands (#611, #4273, #4258); ((ii) Model 1 lacks the Y*i variables, while Model 2 contains the Y*i variables.
. *foreach x of numlist 7 26 27 28 51 61 173 199 200 259 354 606 1002 1013 1035 1046 1062 1068 1070 1074 1079 1084 1107 1108 1112 1173 1190 1193 1206 1238 1279 1280 1286 1289 1293 1304 1306 1312 1315 1340 1352 1353 1361 1363 1381 1385 1407 1408 1411 1441 1447 1480 1706 1792 1793 1806 2041 2082 2115 2119 2141 2150 2219 2231 2328 2339 2349 2357 2371 2540 2546 2572 2583 2631 2776 3020 3104 3195 3229 3427 3437 3551 3556 3557 3564 3630 3634 3635 3953 3957 4007 4013 4027 4066 4078 4088 4096 4116 4119 4121 4124 4128 4137 4140 4143 4156 4158 4164 4166 4192 4196 4223 4253 4257 4259 4269 4271 4280 4283 4291 4310 4339{c -(}
. *oprobit Ycat disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc  intvdempct if (ngo==0 & precmid!=`x'), cluster(precmid)
. *predict prob1_`x' prob2_`x' prob3_`x' prob4_`x' prob5_`x'
. *{c )-}
. *foreach n of numlist 1 2 3 4 5{c -(}
. *gen model1prob_`n'=prob`n'_7 if precmid==7
. *drop prob`n'_7
. *foreach x of numlist 26 27 28 51 61 173 199 200 259 354 606 1002 1013 1035 1046 1062 1068 1070 1074 1079 1084 1107 1108 1112 1173 1190 1193 1206 1238 1279 1280 1286 1289 1293 1304 1306 1312 1315 1340 1352 1353 1361 1363 1381 1385 1407 1408 1411 1441 1447 1480 1706 1792 1793 1806 2041 2082 2115 2119 2141 2150 2219 2231 2328 2339 2349 2357 2371 2540 2546 2572 2583 2631 2776 3020 3104 3195 3229 3427 3437 3551 3556 3557 3564 3630 3634 3635 3953 3957 4007 4013 4027 4066 4078 4088 4096 4116 4119 4121 4124 4128 4137 4140 4143 4156 4158 4164 4166 4192 4196 4223 4253 4257 4259 4269 4271 4280 4283 4291 4310 4339{c -(}
. *replace model1prob_`n'=prob`n'_`x' if precmid==`x'
. *drop prob`n'_`x'
. *{c )-}
. *{c )-}
. 
. *foreach x of numlist 7 26 27 28 51 61 173 199 200 259 354 606  1002 1013 1035 1046 1062 1068 1070 1074 1079 1084 1107 1108 1112 1173 1190 1193 1206 1238 1279 1280 1286 1289 1293 1304 1306 1312 1315 1340 1352 1353 1361 1363 1381 1385 1407 1408 1411 1441 1447 1480 1706 1792 1793 1806 2041 2082 2115 2119 2141 2150 2219 2231 2328 2339 2349 2357 2371 2540 2546 2572 2583 2631 2776 3020 3104 3195 3229 3427 3437 3551 3556 3557 3564 3630 3634 3635 3953 3957 4007 4013 4027 4066 4078 4088 4096 4116 4119 4121 4124 4128 4137 4140 4143 4156 4158 4164 4166 4192 4196 4223 4253 4257  4259 4269 4271  4280 4283 4291 4310 4339{c -(}
. *oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc  intvdempct if (ngo==0 & precmid!=`x'), cluster(precmid)
. *predict prob1_`x' prob2_`x' prob3_`x' prob4_`x' prob5_`x'
. *{c )-}
. *foreach n of numlist 1 2 3 4 5{c -(}
. *gen model2prob_`n'=prob`n'_7 if precmid==7
. *drop prob`n'_7
. *foreach x of numlist 26 27 28 51 61 173 199 200 259 354 606  1002 1013 1035 1046 1062 1068 1070 1074 1079 1084 1107 1108 1112 1173 1190 1193 1206 1238 1279 1280 1286 1289 1293 1304 1306 1312 1315 1340 1352 1353 1361 1363 1381 1385 1407 1408 1411 1441 1447 1480 1706 1792 1793 1806 2041 2082 2115 2119 2141 2150 2219 2231 2328 2339 2349 2357 2371 2540 2546 2572 2583 2631 2776 3020 3104 3195 3229 3427 3437 3551 3556 3557 3564 3630 3634 3635 3953 3957 4007 4013 4027 4066 4078 4088 4096 4116 4119 4121 4124 4128 4137 4140 4143 4156 4158 4164 4166 4192 4196 4223 4253 4257  4259 4269 4271  4280 4283 4291 4310 4339{c -(}
. *replace model2prob_`n'=prob`n'_`x' if precmid==`x'
. *drop prob`n'_`x'
. *{c )-}
. *{c )-}
. 
. *Brier scores.
. *A brier score is the mean squared difference between the predicted probability and the observed outcome. So lower values are better predictions.
. *Table C1.
. oprobit Ycat Ystar1 Ystar3 Ystar4 disp_maj disp_endriv cincratio hostlev fatality postcw igoint coalint  intvmaxpctmembercinc intvdempct if (ngo==0 & precmid!=611 & precmid!=4273 & precmid!=4258), cluster(precmid)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-767.52686}  
Iteration 1:{space 3}log pseudolikelihood = {res:-701.20521}  
Iteration 2:{space 3}log pseudolikelihood = {res:-700.86209}  
Iteration 3:{space 3}log pseudolikelihood = {res:-700.86208}  
{res}
{txt}Ordered probit regression{col 49}Number of obs{col 67}= {res}       686
{txt}{col 49}Wald chi2({res}13{txt}){col 67}= {res}     84.27
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-700.86208{txt}{col 49}Pseudo R2{col 67}= {res}    0.0869

{txt}{ralign 86:(Std. Err. adjusted for {res:98} clusters in precmid)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}                Ycat{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      z{col 54}   P>|z|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Ystar1 {c |}{col 22}{res}{space 2}-.4848414{col 34}{space 2} .2470665{col 45}{space 1}   -1.96{col 54}{space 3}0.050{col 62}{space 4}-.9690829{col 75}{space 3}-.0005999
{txt}{space 14}Ystar3 {c |}{col 22}{res}{space 2}-.8314399{col 34}{space 2} .2926787{col 45}{space 1}   -2.84{col 54}{space 3}0.005{col 62}{space 4} -1.40508{col 75}{space 3}-.2578002
{txt}{space 14}Ystar4 {c |}{col 22}{res}{space 2} .9001945{col 34}{space 2} .3359751{col 45}{space 1}    2.68{col 54}{space 3}0.007{col 62}{space 4} .2416955{col 75}{space 3} 1.558694
{txt}{space 12}disp_maj {c |}{col 22}{res}{space 2}-.2768103{col 34}{space 2} .1645555{col 45}{space 1}   -1.68{col 54}{space 3}0.093{col 62}{space 4}-.5993331{col 75}{space 3} .0457125
{txt}{space 9}disp_endriv {c |}{col 22}{res}{space 2}-.2602174{col 34}{space 2}  .161389{col 45}{space 1}   -1.61{col 54}{space 3}0.107{col 62}{space 4} -.576534{col 75}{space 3} .0560992
{txt}{space 11}cincratio {c |}{col 22}{res}{space 2}-.1407055{col 34}{space 2} .2288641{col 45}{space 1}   -0.61{col 54}{space 3}0.539{col 62}{space 4}-.5892708{col 75}{space 3} .3078598
{txt}{space 13}hostlev {c |}{col 22}{res}{space 2} .1991746{col 34}{space 2} .1852141{col 45}{space 1}    1.08{col 54}{space 3}0.282{col 62}{space 4}-.1638383{col 75}{space 3} .5621875
{txt}{space 12}fatality {c |}{col 22}{res}{space 2}-.0286276{col 34}{space 2} .0388916{col 45}{space 1}   -0.74{col 54}{space 3}0.462{col 62}{space 4}-.1048538{col 75}{space 3} .0475986
{txt}{space 14}postcw {c |}{col 22}{res}{space 2} .1775439{col 34}{space 2} .1736102{col 45}{space 1}    1.02{col 54}{space 3}0.306{col 62}{space 4}-.1627258{col 75}{space 3} .5178137
{txt}{space 14}igoint {c |}{col 22}{res}{space 2} .5517535{col 34}{space 2} .2117931{col 45}{space 1}    2.61{col 54}{space 3}0.009{col 62}{space 4} .1366467{col 75}{space 3} .9668603
{txt}{space 13}coalint {c |}{col 22}{res}{space 2} .3876785{col 34}{space 2} .2912697{col 45}{space 1}    1.33{col 54}{space 3}0.183{col 62}{space 4}-.1831997{col 75}{space 3} .9585567
{txt}intvmaxpctmembercinc {c |}{col 22}{res}{space 2} .8373654{col 34}{space 2} .3222976{col 45}{space 1}    2.60{col 54}{space 3}0.009{col 62}{space 4} .2056738{col 75}{space 3} 1.469057
{txt}{space 10}intvdempct {c |}{col 22}{res}{space 2} -.319527{col 34}{space 2} .2282801{col 45}{space 1}   -1.40{col 54}{space 3}0.162{col 62}{space 4}-.7669478{col 75}{space 3} .1278938
{txt}{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}/cut1 {c |}{col 22}{res}{space 2} .7032914{col 34}{space 2} .7539605{col 62}{space 4}-.7744441{col 75}{space 3} 2.181027
{txt}{space 15}/cut2 {c |}{col 22}{res}{space 2} 2.067536{col 34}{space 2} .7291323{col 62}{space 4} .6384634{col 75}{space 3} 3.496609
{txt}{space 15}/cut3 {c |}{col 22}{res}{space 2} 2.179466{col 34}{space 2} .7264324{col 62}{space 4} .7556846{col 75}{space 3} 3.603247
{txt}{space 15}/cut4 {c |}{col 22}{res}{space 2} 2.428464{col 34}{space 2} .7393373{col 62}{space 4}   .97939{col 75}{space 3} 3.877539
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. brier Ycat1 model1prob_1 if e(sample)

{txt}Mean probability of outcome  {res} 0.4665
{txt}                 of forecast {res} 0.5657

{txt}Correlation                  {res} 0.0775
{txt}ROC area                     {res} 0.5431{txt}  p ={res} 0.0257

{txt}Brier score                  {res} 0.2686
{txt}Spiegelhalter's z-statistic  {res} 8.2121{txt}  p ={res} 0.0000
{txt}Sanders-modified Brier score {res} 0.2683
{txt}Sanders resolution           {res} 0.2354
{txt}Outcome index variance       {res} 0.2489
{txt}Murphy resolution            {res} 0.0135
{txt}Reliability-in-the-small     {res} 0.0329
{txt}Forecast variance            {res} 0.0211
{txt}Excess forecast variance     {res} 0.0210
{txt}Minimum forecast variance    {res} 0.0001
{txt}Reliability-in-the-large     {res} 0.0098
{txt}2*Forecast-Outcome-Covar     {res} 0.0112
{txt}
{com}. brier Ycat1 model2prob_1 if e(sample)

{txt}Mean probability of outcome  {res} 0.4665
{txt}                 of forecast {res} 0.5481

{txt}Correlation                  {res} 0.1495
{txt}ROC area                     {res} 0.5874{txt}  p ={res} 0.0000

{txt}Brier score                  {res} 0.2588
{txt}Spiegelhalter's z-statistic  {res} 7.0234{txt}  p ={res} 0.0000
{txt}Sanders-modified Brier score {res} 0.2579
{txt}Sanders resolution           {res} 0.2346
{txt}Outcome index variance       {res} 0.2489
{txt}Murphy resolution            {res} 0.0143
{txt}Reliability-in-the-small     {res} 0.0233
{txt}Forecast variance            {res} 0.0283
{txt}Excess forecast variance     {res} 0.0277
{txt}Minimum forecast variance    {res} 0.0006
{txt}Reliability-in-the-large     {res} 0.0067
{txt}2*Forecast-Outcome-Covar     {res} 0.0251
{txt}
{com}. brier Ycat2 model1prob_2 if e(sample)

{txt}Mean probability of outcome  {res} 0.4009
{txt}                 of forecast {res} 0.3327

{txt}Correlation                  {res} 0.0331
{txt}ROC area                     {res} 0.5150{txt}  p ={res} 0.2524

{txt}Brier score                  {res} 0.2488
{txt}Spiegelhalter's z-statistic  {res} 5.3986{txt}  p ={res} 0.0000
{txt}Sanders-modified Brier score {res} 0.2492
{txt}Sanders resolution           {res} 0.2312
{txt}Outcome index variance       {res} 0.2402
{txt}Murphy resolution            {res} 0.0089
{txt}Reliability-in-the-small     {res} 0.0180
{txt}Forecast variance            {res} 0.0066
{txt}Excess forecast variance     {res} 0.0066
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0046
{txt}2*Forecast-Outcome-Covar     {res} 0.0026
{txt}
{com}. brier Ycat2 model2prob_2 if e(sample)

{txt}Mean probability of outcome  {res} 0.4009
{txt}                 of forecast {res} 0.3436

{txt}Correlation                  {res} 0.0575
{txt}ROC area                     {res} 0.5375{txt}  p ={res} 0.0478

{txt}Brier score                  {res} 0.2469
{txt}Spiegelhalter's z-statistic  {res} 5.1544{txt}  p ={res} 0.0000
{txt}Sanders-modified Brier score {res} 0.2469
{txt}Sanders resolution           {res} 0.2304
{txt}Outcome index variance       {res} 0.2402
{txt}Murphy resolution            {res} 0.0098
{txt}Reliability-in-the-small     {res} 0.0165
{txt}Forecast variance            {res} 0.0088
{txt}Excess forecast variance     {res} 0.0087
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0033
{txt}2*Forecast-Outcome-Covar     {res} 0.0053
{txt}
{com}. brier Ycat3 model1prob_3 if e(sample)

{txt}Mean probability of outcome  {res} 0.0204
{txt}                 of forecast {res} 0.0116

{txt}Correlation                  {res} 0.0622
{txt}ROC area                     {res} 0.6699{txt}  p ={res} 0.0147

{txt}Brier score                  {res} 0.0200
{txt}Spiegelhalter's z-statistic  {res} 2.1482{txt}  p ={res} 0.0159
{txt}Sanders-modified Brier score {res} 0.0200
{txt}Sanders resolution           {res} 0.0193
{txt}Outcome index variance       {res} 0.0200
{txt}Murphy resolution            {res} 0.0007
{txt}Reliability-in-the-small     {res} 0.0007
{txt}Forecast variance            {res} 0.0000
{txt}Excess forecast variance     {res} 0.0000
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0001
{txt}2*Forecast-Outcome-Covar     {res} 0.0001
{txt}
{com}. brier Ycat3 model2prob_3 if e(sample)

{txt}Mean probability of outcome  {res} 0.0204
{txt}                 of forecast {res} 0.0111

{txt}Correlation                  {res} 0.0819
{txt}ROC area                     {res} 0.7135{txt}  p ={res} 0.0031

{txt}Brier score                  {res} 0.0200
{txt}Spiegelhalter's z-statistic  {res} 2.3352{txt}  p ={res} 0.0098
{txt}Sanders-modified Brier score {res} 0.0200
{txt}Sanders resolution           {res} 0.0188
{txt}Outcome index variance       {res} 0.0200
{txt}Murphy resolution            {res} 0.0012
{txt}Reliability-in-the-small     {res} 0.0012
{txt}Forecast variance            {res} 0.0000
{txt}Excess forecast variance     {res} 0.0000
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0001
{txt}2*Forecast-Outcome-Covar     {res} 0.0001
{txt}
{com}. brier Ycat4 model1prob_4 if e(sample)

{txt}Mean probability of outcome  {res} 0.0379
{txt}                 of forecast {res} 0.0355

{txt}Correlation                  {res}-0.0943
{txt}ROC area                     {res} 0.3656{txt}  p ={res} 0.9900

{txt}Brier score                  {res} 0.0376
{txt}Spiegelhalter's z-statistic  {res} 0.5760{txt}  p ={res} 0.2823
{txt}Sanders-modified Brier score {res} 0.0375
{txt}Sanders resolution           {res} 0.0349
{txt}Outcome index variance       {res} 0.0365
{txt}Murphy resolution            {res} 0.0016
{txt}Reliability-in-the-small     {res} 0.0026
{txt}Forecast variance            {res} 0.0004
{txt}Excess forecast variance     {res} 0.0004
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0000
{txt}2*Forecast-Outcome-Covar     {res}-0.0007
{txt}
{com}. brier Ycat4 model2prob_4 if e(sample)

{txt}Mean probability of outcome  {res} 0.0379
{txt}                 of forecast {res} 0.0430

{txt}Correlation                  {res} 0.0253
{txt}ROC area                     {res} 0.5313{txt}  p ={res} 0.2940

{txt}Brier score                  {res} 0.0370
{txt}Spiegelhalter's z-statistic  {res}-0.5175{txt}  p ={res} 0.6976
{txt}Sanders-modified Brier score {res} 0.0369
{txt}Sanders resolution           {res} 0.0355
{txt}Outcome index variance       {res} 0.0365
{txt}Murphy resolution            {res} 0.0009
{txt}Reliability-in-the-small     {res} 0.0013
{txt}Forecast variance            {res} 0.0007
{txt}Excess forecast variance     {res} 0.0007
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0000
{txt}2*Forecast-Outcome-Covar     {res} 0.0003
{txt}
{com}. brier Ycat5 model1prob_5 if e(sample)

{txt}Mean probability of outcome  {res} 0.0743
{txt}                 of forecast {res} 0.0544

{txt}Correlation                  {res} 0.0382
{txt}ROC area                     {res} 0.5494{txt}  p ={res} 0.1199

{txt}Brier score                  {res} 0.0703
{txt}Spiegelhalter's z-statistic  {res} 2.9309{txt}  p ={res} 0.0017
{txt}Sanders-modified Brier score {res} 0.0701
{txt}Sanders resolution           {res} 0.0670
{txt}Outcome index variance       {res} 0.0688
{txt}Murphy resolution            {res} 0.0018
{txt}Reliability-in-the-small     {res} 0.0031
{txt}Forecast variance            {res} 0.0019
{txt}Excess forecast variance     {res} 0.0019
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0004
{txt}2*Forecast-Outcome-Covar     {res} 0.0009
{txt}
{com}. brier Ycat5 model2prob_5 if e(sample)

{txt}Mean probability of outcome  {res} 0.0743
{txt}                 of forecast {res} 0.0542

{txt}Correlation                  {res} 0.0400
{txt}ROC area                     {res} 0.5373{txt}  p ={res} 0.1876

{txt}Brier score                  {res} 0.0708
{txt}Spiegelhalter's z-statistic  {res} 3.2276{txt}  p ={res} 0.0006
{txt}Sanders-modified Brier score {res} 0.0695
{txt}Sanders resolution           {res} 0.0673
{txt}Outcome index variance       {res} 0.0688
{txt}Murphy resolution            {res} 0.0015
{txt}Reliability-in-the-small     {res} 0.0022
{txt}Forecast variance            {res} 0.0027
{txt}Excess forecast variance     {res} 0.0027
{txt}Minimum forecast variance    {res} 0.0000
{txt}Reliability-in-the-large     {res} 0.0004
{txt}2*Forecast-Outcome-Covar     {res} 0.0011
{txt}
{com}. 
. *In addition, we can compare the predicted probabilities of Y=z when we know Y to be z. Higher values are better predictions, since it means more often predicting the true value of Y.
. *Table C2
. sum model1prob_1 if Ycat==1 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model1prob_1 {c |}{res}        320    .5777671    .1474421   .2610619   .8516715
{txt}
{com}. sum model2prob_1 if Ycat==1 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model2prob_1 {c |}{res}        320    .5749778    .1543804   .1473935   .8857111
{txt}
{com}. sum model1prob_2 if Ycat==2 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model1prob_2 {c |}{res}        275    .3360265    .0760981   .1470916   .4563088
{txt}
{com}. sum model2prob_2 if Ycat==2 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model2prob_2 {c |}{res}        275    .3501479    .0922475   .1076711   .4768855
{txt}
{com}. sum model1prob_3 if Ycat==3 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model1prob_3 {c |}{res}         14    .0139376    .0030969   .0069968    .018171
{txt}
{com}. sum model2prob_3 if Ycat==3 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model2prob_3 {c |}{res}         14     .014452    .0038691   .0042609   .0186143
{txt}
{com}. sum model1prob_4 if Ycat==4 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model1prob_4 {c |}{res}         26     .026194    .0145004   .0089875   .0617503
{txt}
{com}. sum model2prob_4 if Ycat==4 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model2prob_4 {c |}{res}         26    .0464784    .0293047   .0070086   .1073463
{txt}
{com}. sum model1prob_5 if Ycat==5 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model1prob_5 {c |}{res}         51    .0602878    .0454408   .0073339   .1987304
{txt}
{com}. sum model2prob_5 if Ycat==5 & e(sample)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
model2prob_5 {c |}{res}         51    .0615253     .053072   .0024741    .203656
{txt}
{com}. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/Owsiak/Dropbox/Diehl Greig and Owsiak/II 2019/Individual Article/Final Files/Log File for Trajectories - Theory and Evidence.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}29 Jul 2020, 12:05:58
{txt}{.-}
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{txt}{sf}{ul off}